most citedGemma 4 Technical Report

3 citations · 5 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026★ 3 cited

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…

cs.CL2026

Rethinking Scientific Discovery in the Agentic Era

Yining Zheng, Yuxin Wang, Jiahao Lu +27

Artificial intelligence has advanced scientific discovery, but most AI4Science systems remain fragmented tools that rely on humans to coordinate problem formulation, literature gro…

cs.AI2026

AstroAgentBench: Evaluating Agentic Planning on Space Mission Planning Tasks

Weiyi Wang, Xinchi Chen, Jingjing Gong +2

Recent LLM-for-Space systems address mission planning, scheduling, operations support, simulator control, and autonomy, but their evaluations use different task contracts, control…

cs.CL2025★ 2 cited

EmbeddingGemma: Powerful and Lightweight Text Representations

Henrique Schechter Vera, Sahil Dua, Biao Zhang +86

We introduce EmbeddingGemma, a new lightweight, open text embedding model based on the Gemma 3 language model family. Our innovative training recipe strategically captures knowledg…

cs.SE2025

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Zeyu Sun, Jingjing Liang, Weiyi Wang +3

MLIR (Multi-Level Intermediate Representation) has rapidly become a foundational technology for modern compiler frameworks, enabling extensibility across diverse domains. However,…

cs.RO2025

Boosting Zero-Shot VLN via Abstract Obstacle Map-Based Waypoint Prediction with TopoGraph-and-VisitInfo-Aware Prompting

Boqi Li, Siyuan Li, Weiyi Wang +3

With the rapid progress of foundation models and robotics, vision-language navigation (VLN) has emerged as a key task for embodied agents with broad practical applications. We addr…

cs.LG2025

Taming Hyperparameter Sensitivity in Data Attribution: Practical Selection Without Costly Retraining

Weiyi Wang, Junwei Deng, Yuzheng Hu +5

Data attribution methods, which quantify the influence of individual training data points on a machine learning model, have gained increasing popularity in data-centric application…